In the mobile networks, the traffic load is non-uniformly distributed. Some geographical areas in the peak hour will have unusually high traffic density which will suffer from negative impacts such as high amount of blocked calls, high packet dropping rate, etc. It's important for the network operator to address such problem to keep the network performance in every area at a satisfactory level. The main method is load balancing, which migrates the load of hot-spot base station to other less congested base stations. Considering the large amount of base stations and different traffic load in different base stations, an efficient load balancing scheme is needed for the cellular network to avoid local congestion and to provide better quality of service in every area, in order to increase system performance. Previous studies use different technologies, such as cell-breathing, channel borrowing or dynamic scheduling, to address the load balancing problem.
Existing solutions, including cell-breathing, channel borrowing, or dynamic scheduling, mostly focused on local optimization problem which only takes the neighbor base stations into consideration when making the load-balancing decision. The main reason is that considering the current network architecture, the network control unit only has a limited knowledge of local network which could only support locally distributed load balancing schemes. However, as it can be seen from real traffic traces and the probability that the neighbor base stations also suffering excessive load is high, the efficiency of such efforts is greatly reduced. This situation now can change thanks to newly proposed Cloud-Radio Access Network (C-RAN) architecture.
C-RAN is a centralized processing, cooperative radio, and Cloud infrastructure Radio Access Network. The main architecture of C-RAN is composed of a distributed radio network with Remote Radio Heads, a centralized BaseBand Unit (BBU) pool using virtualization technology and a network connecting these two parts. All the BBUs and other site control equipments are aggregated in a centralized place in C-RAN's architecture, which provides a great convenience for sharing information between base stations and for centralized network management. For load balancing problem, such aggregation feature provides an important opportunity for centralized global load balancing which balance the load exploiting the whole network load knowledge, i.e., the global knowledge.
Therefore, there is a need for an efficient load balancing method for the C-RAN.